New Mexico Computer Science for AllAgent-based modelingBy Irene LeeDecember 27, 2012

Agent-based Modeling of Complex Adaptive Systems

Using agent-based modeling (ABM) tools, we are able to model complex adaptive systems.

An example: termites modelThe model consists of agents, an environ- ment, and interactions between agents and environment.The system is adaptive and changes over time. ABM generates “emergent” patterns.

Agent-based modeling: a tool for studying complex adaptive systems

Agent-based modeling paradigm

The “Observer”– instantiates the world The “Turtles”– the agents The “Patches” – the environment

Agent based modeling phases Setup– instantiation of world Runtime loop – the agents put into

motion. Exit

Agent-based modeling Abstractions

Agents with rules Environment or space in which they exist Time

NetLogo is a programming language

Creating Computer Models with NetLogo

Creating Computer Models with NetLogo

Creating Computer Models with NetLogo

Modeling and Computational Science

•A model is a representation of the interaction of real-world objects in a complex system.

•The goal is to gain an understanding of how the model’s results relate to real-world phenomena.

•Random factors built into the model and variables changed by the user cause different results to be generated when the model is run repeatedly.

Idea Models e.g. Model of Predator and Prey

Minimal Models for Systems e.g. Model of Wolves and Caribou

Systems Models / Large scale ? e.g. Model of every Wolf and Caribou in 5

square mile section of Yellowstone

*This classification scheme was proposed by J. Roughgarden.

Increasing complexity, detail and specificity

Model Classification Scheme*

• learning about models and modeling• conduct experiments by changing variables,

collecting data, and analyzing results.

• deconstruct models into agents, behaviors, environment, and interactions.

• develop expertise in evaluating models• coding/decoding skills and sustained

reasoning

• Abstraction of a real-world problem into a computer model suitable for testing hypotheses.

• Evaluation of model, choice of assumptions, and findings.

A Progression for Learning about Modeling

Use

Modify

Create

Scientific Inquiry / Critical thinking skillsStudents as creators and young researchersUnderstanding the use of computers in

STEM fieldsPreparation for future endeavors in

computingBuilding an understanding of complex

systems

Preparation for STEM futures

Concepts that modelers must understand to deconstruct

and eventually write agent based models are: 1) states 2) variables3) data structures4) rules, logic and control structures, Boolean operations5) iteration and recursion6) functions, procedures, subroutines 7) syntax of programming 8) interface design9) data analysis (import/export and plot data)10) parallelism.

Preparation for Computer Science